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International Conference Image Analysis and Recognition

ICIAR 2008: Image Analysis and Recognition pp 537–546Cite as

An Algorithm for Binary Contour Objects Representation and Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5112))

Abstract

Representation of an object in image for machine learning applications (recognition, retrieval, identification, etc.) has to be based on a previously chosen feature. Binary shape is a very popular and commendable one. It has many advantages and can be successfully used in many applications, especially in engineering. To achieve better characteristics, various shape transformations are used. Obviously, they should be robust to as many shape deformations as it is possible. In this paper results of exhaustive exploration of a new method are presented. This method is based on transformation from Cartesian to polar coordinates, but it overcomes few problems, that were not solved yet. Above all, the proposed transform is more robust to occlusion and noise, two the most challenging problems.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Systems, Szczecin University of Technology, Zolnierska 49, 71-210, Szczecin, Poland

    Dariusz Frejlichowski

Authors
  1. Dariusz Frejlichowski
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Aurélio Campilho Mohamed Kamel

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© 2008 Springer-Verlag Berlin Heidelberg

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Frejlichowski, D. (2008). An Algorithm for Binary Contour Objects Representation and Recognition. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_53

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  • DOI: https://doi.org/10.1007/978-3-540-69812-8_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69811-1

  • Online ISBN: 978-3-540-69812-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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